Osteoarthritis Synovial Tissue Research Articles

Peptidoglycan in osteoarthritis synovial tissue is associated with joint inflammation

ObjectivesPeptidoglycan (PG) is an arthritogenic bacterial cell wall component whose role in human osteoarthritis is poorly understood. The purpose of this study was to determine if PG is present in synovial tissue of osteoarthritis patients at the time of primary total knee arthroplasty (TKA), and if its presence is associated with inflammation and patient reported outcomes.MethodsIntraoperative synovial tissue and synovial fluid samples were obtained from 56 patients undergoing primary TKA, none of whom had history of infection. PG in synovial tissue was detected by immunohistochemistry (IHC) and immunofluorescence microscopy (IFM). Synovial tissue inflammation and fibrosis were assessed by histopathology and synovial fluid cytokine quantification. Primary human fibroblasts isolated from arthritis synovial tissue were stimulated with PG to determine inflammatory cytokine response.ResultsA total of 33/56 (59%) of primary TKA synovial tissue samples were positive for PG by IHC, and PG staining colocalized with markers of synovial macrophages and fibroblasts by IFM. Synovial tissue inflammation and elevated IL-6 in synovial fluid positively correlated with PG positivity. Primary human fibroblasts stimulated with PG secreted high levels of IL-6, consistent with ex vivo findings. Interestingly, we observed a significant inverse correlation between PG and age at time of TKA, indicating younger age at time of TKA was associated with higher PG levels.ConclusionPeptidoglycan is commonly found in synovial tissue from patients undergoing TKA. Our data indicate that PG may play an important role in inflammatory synovitis, particularly in patients who undergo TKA at a relatively younger age.

Deep learning for synovial volume segmentation of the first carpometacarpal joint in osteoarthritis patients

ObjectiveThe objective of this study was to develop a deep-learning-based approach to automatically segment 3D ultrasound images of the synovial tissue in osteoarthritis of the first carpometacarpal (CMC1 OA). DesignDeep learning predictions on 2D ultrasound slices sampled in the transverse plane were used to view the synovial tissue of the first carpometacarpal in patients with OA, followed by reconstruction into 3D surfaces. A modified 2D U-Net was trained using a dataset of 832 2D US images resliced from 89 3D US images. Segmentation accuracy was evaluated using a testing dataset of 208 2D US images resliced from 15 3D US images. Absolute and signed performance metrics were computed, and segmentation performance was compared between the manual segmentations of raters 1 and 2. ResultsResults of the U-Net-based run were mean 3D DSC 86.9 ± 4.8%, recall 93.7 ± 3.6%, precision 81.1 ± 6.9%, volume percent difference 16.9 ± 10.2%, mean surface distance 0.18 ± 0.04 mm, and Hausdorff distance 1.8 ± 0.8 mm. The algorithm demonstrated an overall increase in performance after 3D segmentation reconstruction compared to 2D predictions, but the difference was not statistically significant. ConclusionThis study investigated the use of a modified U-Net algorithm to automatically segment the synovial tissue volume (STV) of CMC1 OA patients and demonstrated that the addition of this deep learning method increases the efficiency of STV estimations in clinical trial settings.

Proopiomelanocortin and its potential functions in the pathological synovium of patients with osteoarthritis.

Osteoarthritis (OA) is a chronic degenerative disease of the joints, adversely affecting the quality of life for the patients. To better understand the mechanisms underlying the pathological changes in osteoarthritis and identify the key genes associated with osteoarthritis pathogenesis, we utilized a comprehensive bioinformatics approach to analyze the transcriptome between osteoarthritis synovial and control samples with public microarray datasets. First, the GSE82107 microarray dataset containing ten osteoarthritis synovial and seven control samples were selected from the Gene Expression Omnibus (GEO) database. A total of 52 overlapped differentially expressed genes (DEGs) in GSE82107 and OA-associated genes in the Comparative Toxicogenomics Database were identified. These OA-associated DEGs were further incorporated into a protein-protein interaction (PPI) network. Gene proopiomelanocortin (POMC) was identified in the largest cluster of PPI network with Cytoscape. GO and KEGG analyses suggested that these genes were associated with multiple functions. Other GEO datasets of osteoarthritis synovial tissues, including GSE55235 and GSE55457, were used to validate the expression level of POMC. Quantitative polymerase chain reaction and western blot analyses were also used to test the expression levels of POMC in our osteoarthritis samples. We found POMC was positively associated with transporter complex, ion channel activity, and G protein-coupled receptor signaling pathway. This study highlighted the OA-associated gene POMC, and its related biological pathways, suggesting it served as a potential treatment target in osteoarthritis.

Exploring CircRNA N6-methyladenosine in human rheumatoid arthritis: Hyper-methylated hsa_circ_0007259 as a potential biomarker and its involvement in the hsa_circ_0007259/hsa_miR-21-5p/STAT3 axis

BackgroundN6-methyladenosine (m6A) is a highly enriched modification found in circular RNAs (CircRNAs); however, the ability and mechanism of CircRNAs to encode for m6A function in rheumatoid arthritis (RA) remain poorly understood. MethodsWe utilized an epitranscriptomic microarray to measure levels and quantities of m6A methylated CircRNAs in synovial tissues of patients with RA and osteoarthritis (OA). We then utilized methylated RNA immunoprecipitation- and MazF-quantitative PCR to identify and validate differentially m6A-methylated RNAs between the groups, conducted a functional enrichment analysis, and selected protein–protein interaction hub genes. Lastly, we predicted and validated the CircRNA/miRNA/mRNA interaction networks. ResultsWe detected 4,845 CircRNAs containing m6A in our samples, with 53 CircRNAs upregulated, and 139 CircRNAs downregulated compared to human OA synovial tissue (|fold change| ≥ 1.2 and p ≤ 0.05). The differentially m6A-modified CircRNAs were associated with the interleukin-6-mediated signaling pathway, with an increase in relative m6A-methylated levels of hsa_circ_0007259 in human RA, a significant decrease in hsa_miR-21-5p, and an increase in signal transducer and activator of transcription 3（STAT3）. The Luciferase Reporter Gene assay verified the binding of hsa_circ_0007259 to hsa_miR-21-5p and the subsequent binding of hsa_miR-21-5p to STAT3. ConclusionWe showed a notable increase in the relative m6A-methylated levels of hsa_circ_0007259 in human RA, indicating a potential role of hypermethylated hsa_circ_0007259 in RA pathogenesis. This may provide valuable insight into the mechanism of RA and the possibility of utilizing hsa_circ_0007259 as a valuable biomarker.

Regulatory effect of zinc finger protein A20 on rheumatoid arthritis through NLRP3/Caspase-1 signaling axis mediating pyroptosis of HFLS- RA cells.

As a chronic inflammatory autoimmune disease, rheumatoid arthritis (RA) causes significant destruction to joints and cartilage. So far, from RA patients, the synovial cells and subsynovial tissues reflected the positive expression of IL-18, IL-1β, Caspase-1 and NLRP3, with the synovial tissues of those patients also expressing the zinc finger protein A20 at a significantly lower level compared with osteoarthritis (OA) ones. Thus, the inhibition of the NLRP3/caspase-1 signaling pathway can effectively down-regulate the expression of IL-1β, but when NLRP3 inflammasomes are activated, they can also shear GSDMD and induce pyroptosis. These suggest that the Gasdermin family of proteins, downstream of the NLRP3 inflammasome, could be involved in pyroptosis. Previous studies have shown that A20 contributes largely as an anti-inflammatory factor in many inflammatory diseases, but it remains unclear whether zinc finger protein A20, as an inhibitor of NLRP3 inflammasomes, can play a protective role against RA by inhibiting NLRP3 inflammasome-mediated pyroptosis. Therefore, this study aimed to verify the effects of zinc finger protein A20 on NLRP3/ Caspase-1-mediated pyroptosis in rheumatoid arthritis synovial fibroblasts (HFLS-RA) cells through cell experiments and clinical bidirectional verification, aim to understand the regulatory mechanism of A20 on RA. The results of clinical trials showed that NLRP3, Caspase-1, IL-1β and IL-18 were positively scattered in RA synovial cells and subsynovial tissue. The expression level of the zinc finger protein A20 in RA synovial tissues was significantly lower than that in OA synovial tissue and was negative, while zinc finger protein A20 was strongly positive in OA synovial tissue. In addition, HFLS-RA cells with siRNA-interfering zinc finger protein A20 were constructed at the cellular level, with the results also confirming that zinc finger protein A20 can play a protective role against RA by inhibiting NLRP3 inflammasome-mediated pyroptosis. In conclusion, this study is of great significance for understanding the role of the NLRP3-caspase-1-IL-1β/ pyroptosis signaling pathway in the occurrence and development of RA. It is expected that the results will provide a theoretical basis for the immune regulation of innate immunity in the occurrence and development of RA, while providing a new therapeutic target for the clinical treatment of RA.

Identification of aging-related biomarkers and immune infiltration characteristics in osteoarthritis based on bioinformatics analysis and machine learning.

Osteoarthritis (OA) is a degenerative disease closely related to aging. Nevertheless, the role and mechanisms of aging in osteoarthritis remain unclear. This study aims to identify potential aging-related biomarkers in OA and to explore the role and mechanisms of aging-related genes and the immune microenvironment in OA synovial tissue. Normal and OA synovial gene expression profile microarrays were obtained from the Gene Expression Omnibus (GEO) database and aging-related genes (ARGs) from the Human Aging Genomic Resources database (HAGR). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Disease Ontology (DO), and Gene set variation analysis (GSVA) enrichment analysis were used to uncover the underlying mechanisms. To identify Hub ARDEGs with highly correlated OA features (Hub OA-ARDEGs), Weighted Gene Co-expression Network Analysis (WGCNA) and machine learning methods were used. Furthermore, we created diagnostic nomograms and receiver operating characteristic curves (ROC) to assess Hub OA-ARDEGs' ability to diagnose OA and predict which miRNAs and TFs they might act on. The Single sample gene set enrichment analysis (ssGSEA) algorithm was applied to look at the immune infiltration characteristics of OA and their relationship with Hub OA-ARDEGs. We discovered 87 ARDEGs in normal and OA synovium samples. According to functional enrichment, ARDEGs are primarily associated with inflammatory regulation, cellular stress response, cell cycle regulation, and transcriptional regulation. Hub OA-ARDEGs with excellent OA diagnostic ability were identified as MCL1, SIK1, JUND, NFKBIA, and JUN. Wilcox test showed that Hub OA-ARDEGs were all significantly downregulated in OA and were validated in the validation set and by qRT-PCR. Using the ssGSEA algorithm, we discovered that 15 types of immune cell infiltration and six types of immune cell activation were significantly increased in OA synovial samples and well correlated with Hub OA-ARDEGs. Synovial aging may promote the progression of OA by inducing immune inflammation. MCL1, SIK1, JUND, NFKBIA, and JUN can be used as novel diagnostic biomolecular markers and potential therapeutic targets for OA.

Effects of synovial macrophages in osteoarthritis.

Osteoarthritis (OA) is a common degenerative disease in mammals. However, its pathogenesis remains unclear. Studies indicate that OA is not only an aging process that but also an inflammation-related disease. Synovitis is closely related to the progression of OA, and synovial macrophages are crucial participants in synovitis. Instead of being a homogeneous population, macrophages are polarized into M1 or M2 subtypes in OA synovial tissues. Polarization is highly associated with OA severity. However, the M1/M2 ratio cannot be the only factor in OA prognosis because intermediate stages of macrophages also exist. To better understand the mechanism of this heterogeneous disease, OA subtypes of synovial macrophages classified by gene expression were examined. Synovial macrophages do not act alone; they interact with surrounding cells such as synovial fibroblasts, osteoclasts, chondrocytes, lymphocytes and even adipose cells through a paracrine approach to exacerbate OA. Treatments targeting synovial macrophages and their polarization are effective in relieving pain and protecting cartilage during OA development. In this review, we describe how synovial macrophages and their different polarization states influence the progression of OA. We summarize the current knowledge of the interactions between macrophages and other joint cells and examine the current research on new medications targeting synovial macrophages.

Fibroblast growth factor 10 delays the progression of osteoarthritis by attenuating synovial fibrosis via inhibition of IL-6/JAK2/STAT3 signaling in vivo and in vitro

Synovial fibrosis is a driver in the progression of osteoarthritis (OA). Fibroblast growth factor 10 (FGF10) has prominent anti-fibrotic effects in many diseases. Thus, we explored the anti-fibrosis effects of FGF10 in OA synovial tissue. In vitro, fibroblast-like synoviocytes (FLSs) were isolated from OA synovial tissue and stimulated with TGF-β to establish a cell model of fibrosis. After treatment with FGF10, we assessed the effects on FLS proliferation and migration using CCK-8, EdU, and scratch assays, and collagen production was observed using Sirius Red Stain. The JAK2/STAT3 pathway and expression of fibrotic markers were evaluated through western blotting (WB) and immunofluorescence (IF). In vivo, we treated mice with OA induced by surgical destabilization of the medial meniscus (DMM) with FGF10 and assessed the anti-OA effect using histological and immunohistochemical (IHC) staining of MMP13, and fibrosis was evaluated using HE and Masson's trichrome staining. The expression of IL-6/JAK2/STAT3 pathway components was determined using ELISA, WB, IHC, and IF. In vitro, FGF10 inhibited TGF-β-induced FLS proliferation and migration, decreased collagen deposition, and improved synovial fibrosis. Moreover, FGF10 mitigated synovial fibrosis and improved the symptoms of OA in DMM-induced OA mice. Overall, FGF10 had promising anti-fibrotic effects on FLSs and improved OA symptoms in mice. The IL-6/STAT3/JAK2 pathway plays key roles in the anti-fibrosis effect of FGF10. This study is the first to demonstrate that FGF10 inhibited synovial fibrosis and attenuated the progression of OA by inhibiting the IL-6/JAK2/STAT3 pathway.

The GM-CSF/CCL17 pathway in obesity-associated osteoarthritic pain and disease in mice

We have previously identified a granulocyte macrophage-colony stimulating factor (GM-CSF)/C-C motif ligand 17 (CCL17) pathway in monocytes/macrophages, in which GM-CSF regulates the formation of CCL17, and it is important for an experimental osteoarthritis (OA) model. We explore here additional OA models, including in the presence of obesity, such as a requirement for this pathway. The roles of GM-CSF, CCL17, CCR4, and CCL22 in various experimental OA models, including those incorporating obesity (eight-week high-fat diet), were investigated using gene-deficient male mice. Pain-like behavior and arthritis were assessed by relative static weight distribution and histology, respectively. Cell populations (flow cytometry) and cytokine messenger RNA (mRNA) expression (qPCR) in knee infrapatellar fat pad were analyzed. Human OA sera were collected for circulating CCL17 levels (ELISA) and OA knee synovial tissue for gene expression (qPCR). We present evidence that: i) GM-CSF, CCL17, and CCR4, but not CCL22, are required for the development of pain-like behavior and optimal disease in three experimental OA models, as well as for exacerbated OA development due to obesity, ii) obesity alone leads to spontaneous knee joint damage in a GM-CSF- and CCL17-dependent manner, and iii) in knee OA patients, early indications are that BMI correlates with a lower Oxford Knee Score (r=-0.458and p=0.0096), with elevated circulating CCL17 levels (r=0.2108and p=0.0153) and with elevated GM-CSF and CCL17 gene expression in OA synovial tissue. The above findings indicate that GM-CSF, CCL17, and CCR4 are involved in obesity-associated OA development, broadening their potential as targets for possible treatments for OA.

Identification of Diagnostic Markers in Synovial Tissue of Osteoarthritis by Weighted Gene Coexpression Network.

Osteoarthritis (OA) is a serious threat to human health. However, the etiology and pathogenesis of the disease are not fully understood. Most researchers believe that the degeneration and imbalance of articular cartilage, extracellular matrix, and subchondral bone are the fundamental causes of osteoarthritis. However, recent studies have shown that synovial lesions may precede cartilage, which may be an important precipitating factor in the early stage of OA and the whole course of the disease. This study aimed to conduct an analysis based on sequence data from the Gene Expression Omnibus (GEO) database to investigate the presence of effective biomarkers in the synovial tissue of osteoarthritis for the diagnosis and control of OA progression. In this study, the differentially expressed OA-related genes (DE-OARGs) in osteoarthritis synovial tissues were extracted in the GSE55235 and GSE55457 datasets using the Weighted Gene Co-expression Network Analysis (WGCNA) and limma. Least-Absolute Shrinkage and Selection Operator (LASSO) algorithm was used to select the diagnostic genes based on the DE-OARGs by glmnet package. 7 genes were selected as diagnostic genes including SAT1, RLF, MAFF, SIK1, RORA, ZNF529, and EBF2. Subsequently, the diagnostic model was constructed and the results of the Area Under the Curve (AUC) demonstrated that the diagnostic model had high diagnostic performance for OA. Additionally, among the 22 immune cells of the Cell type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) and the 24 immune cells of the single sample Gene Set Enrichment Analysis (ssGSEA), 3 immune cells and 5 immune cells were different between the OA and normal samples, respectively. The expression trends of the 7 diagnostic genes were consistent in the GEO datasets and the results of the real-time reverse transcriptionPCR (qRT-PCR). The results of this study demonstrate that these diagnostic markers have important significance in the diagnosis and treatment of OA, and will provide further evidence for the clinical and functional studies of OA.

Identification and validation of BCL6 and VEGFA as biomarkers and ageing patterns correlating with immune infiltrates in OA progression

Osteoarthritis (OA), the most common type of arthritis, is a complex biological response caused by cartilage wear and synovial inflammation that links biomechanics and inflammation. The progression of OA correlates with a rise in the number of senescent cells in multiple joint tissues. However, the mechanisms by which senescent cells and their involvement with immune infiltration promote OA progression are not fully understood. The gene expression profiles and clinical information of OA and healthy control synovial tissue samples were retrieved from the Gene Expression Omnibus database, and then differential analysis of senescence regulators between OA and normal samples was performed. The random forest (RF) was used to screen candidate senescence regulators to predict the occurrence of OA. The reverse transcription quantitative real-time PCR experiments at tissue’s level was performed to confirm these biomarkers. Moreover, two distinct senescence patterns were identified and systematic correlation between these senescence patterns and immune cell infiltration was analyzed. The senescence score and senescence gene clusters were constructed to quantify senescence patterns together with immune infiltration of individual OA patient. 73 senescence differentially expressed genes were identified between OA patients and normal controls. The RF method was utilized to build an OA risk model based on two senescence related genes: BCL6 and VEGFA. Next, two distinct aging patterns were determined in OA synovial samples. Most patients from senescence cluster A were further classified into gene cluster B and high senescence score group correlated with a non-inflamed phenotype, whereas senescence cluster B were classified into gene cluster A and low senescence score group correlated with an inflamed phenotype. Our study revealed that senescence played an important role in in OA synovial inflammation. Evaluating the senescence patterns of individuals with OA will contribute to enhancing our cognition of immune infiltration characterization, providing novel diagnostic and prognostic biomarkers, and guiding more effective immunotherapy strategies.

Identification and validation of hub genes and potential drugs involved in osteoarthritis through bioinformatics analysis.

Purpose: Osteoarthritis (OA) is a common degenerative disease, which still lacks specific therapeutic drugs. Synovitis is one of the most important pathological process in OA. Therefore, we aim to identify and analyze the hub genes and their related networks of OA synovium with bioinformatics tools to provide theoretical basis for potential drugs. Materials and methods: Two datasets were obtained from GEO. DEGs and hub genes of OA synovial tissue were screened through Gene Ontology (GO) annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment as well as protein-protein interaction (PPI) network analysis. Subsequently, the correlation between expression of hub genes and ferroptosis or pyroptosis was analyzed. CeRNA regulatory network was constructed after predicting the upstream miRNAs and lncRNAs. The validation of hub genes was undertook through RT-qPCR and ELISA. Finally, potential drugs targeting pathways and hub genes were identified, followed by the validation of the effect of two potential drugs on OA. Results: A total of 161 commom DEGs were obtained, of which 8 genes were finally identified as hub genes through GO and KEGG enrichment analysis as well as PPI network analysis. Eight genes related to ferroptosis and pyroptosis respectively were significantly correlated to the expression of hub genes. 24 miRNAs and 69 lncRNAs were identified to construct the ceRNA regulatory network. The validation of EGR1, JUN, MYC, FOSL1, and FOSL2 met the trend of bioinformatics analysis. Etanercept and Iguratimod reduced the secretion of MMP-13 and ADAMTS5 of fibroblast-like synoviocyte. Conclusion: EGR1, JUN, MYC, FOSL1, and FOSL2 were identified as hub genes in the development of OA after series of bioinformatics analysis and validation. Etanercept and Iguratimod seemed to have opportunities to be novel drugs for OA.

Mechanism of immune infiltration in synovial tissue of osteoarthritis: a gene expression-based study

BackgroundOsteoarthritis is a chronic degenerative joint disease, and increasing evidences suggest that the pathogenic mechanism involves immune system and inflammation.AimsThe aim of current study was to uncover hub genes linked to immune infiltration in osteoarthritis synovial tissue using comprehensive bioinformatics analysis and experimental confirmation.MethodsMultiple microarray datasets (GSE55457, GSE55235, GSE12021 and GSE1919) for osteoarthritis in Gene Expression Omnibus database were downloaded for analysis. Differentially expressed genes (DEGs) were identified using Limma package in R software, and immune infiltration was evaluated by CIBERSORT algorithm. Then weighted gene co-expression network analysis (WGCNA) was performed to uncover immune infiltration-associated gene modules. Protein–protein interaction (PPI) network was constructed to select the hub genes, and the tissue distribution of these genes was analyzed using BioGPS database. Finally, the expression pattern of these genes was confirmed by RT-qPCR using clinical samples.ResultsTotally 181 DEGs between osteoarthritis and normal control were screened. Macrophages, mast cells, memory CD4 T cells and B cells accounted for the majority of immune cell composition in synovial tissue. Osteoarthritis synovial showed high abundance of infiltrating resting mast cells, B cells memory and plasma cells. WGCNA screened 93 DEGs related to osteoarthritis immune infiltration. These genes were involved in TNF signaling pathway, IL-17 signaling pathway, response to steroid hormone, glucocorticoid and corticosteroid. Ten hub genes including MYC, JUN, DUSP1, NFKBIA, VEGFA, ATF3, IL-6, PTGS2, IL1B and SOCS3 were selected by using PPI network. Among them, four genes (MYC, JUN, DUSP1 and NFKBIA) specifically expressed in immune system were identified and clinical samples revealed consistent change of these four genes in synovial tissue retrieved from patients with osteoarthritis.ConclusionA 4-gene-based diagnostic model was developed, which had well predictive performance in osteoarthritis. MYC, JUN, DUSP1 and NFKBIA might be biomarkers and potential therapeutic targets in osteoarthritis.

Tensile strain and altered synovial tissue metabolism in human knee osteoarthritis

Synovium is critical for maintaining joint homeostasis and may contribute to mechanobiological responses during joint movement. We investigated mechanobiological responses of whole synovium from patients with late-stage knee osteoarthritis (OA). Synovium samples were collected during total knee arthroplasty and assigned to histopathology or cyclic 10% tensile strain loading, including (1) static (control); (2) low-frequency (0.3 Hz); and iii) high-frequency (1.0 Hz) for 30-min. After 6-h incubation, tissues were bisected for RNA isolation and immunostaining (3-nitrotyrosine; 3-NT). RNA sequencing was analyzed for differentially expressed genes and pathway enrichment. Cytokines and lactate were measured in conditioned media. Compared to controls, low-frequency strain induced enrichment of pathways related to interferon response, Fc-receptor signaling, and cell metabolism. High-frequency strain induced enrichment of pathways related to NOD-like receptor signaling, high metabolic demand, and redox signaling/stress. Metabolic and redox cell stress was confirmed by increased release of lactate into conditioned media and increased 3-NT formation in the synovial lining. Late-stage OA synovial tissue responses to tensile strain include frequency-dependent increases in inflammatory signaling, metabolism, and redox biology. Based on these findings, we speculate that some synovial mechanobiological responses to strain may be beneficial, but OA likely disturbs synovial homeostasis leading to aberrant responses to mechanical stimuli, which requires further validation.

MiR-150-5p and XIST interaction controls monocyte adherence: Implications for osteoarthritis therapy

Recent literature highlights the importance of microRNAs (miRNAs) functioning as diagnostic biomarkers and therapeutic agents in osteoarthritis (OA) and regulators of gene expression. In OA pathogenesis, cell adhesion molecules (CAMs), especially vascular cell adhesion protein 1 (VCAM-1), recruit monocyte infiltration to inflamed synovial tissues and thus accelerate OA progression. Up until now, little has been known about the regulatory mechanisms between miRNAs, long non-coding RNAs (lncRNAs) and VCAM-1 during OA progression. The evidence in this article emphasizes that the functional feature of miR-150-5p is an interaction with the lncRNA X-inactive specific transcript (XIST), which regulates VCAM-1-dependent monocyte adherence in OA synovial fibroblasts (OASFs). Levels of VCAM-1, CD11b (a monocyte marker) and XIST expression were higher in human synovial tissue samples and OASFs, while levels of miR-150-5p were lower in human OA synovial tissue compared with non-OA specimens. XIST enhanced VCAM-1-dependent monocyte adherence to OASFs. Upregulation of miR-150-5p inhibited the effects of XIST upon monocyte adherence. Administration of miR-150-5p effectively ameliorated OA severity in anterior cruciate ligament transection (ACLT) rats. The interaction of miR-150-5p and XIST regulated VCAM-1-dependent monocyte adherence and attenuated OA progression. Our findings suggest that miR-150-5p is a promising small-molecule therapeutic strategy for OA.

RNA-seq characterization of histamine-releasing mast cells as potential therapeutic target of osteoarthritis

ObjectiveMast cells in the osteoarthritis (OA) synovium correlate with disease severity. This study aimed to further elucidate the role of mast cells in OA by RNA-Seq analysis and pharmacological blockade of the activity of histamine, a key mast cell mediator, in murine OA. MethodsWe examined OA synovial tissues and fluids by flow cytometry, immunostaining, single-cell and bulk RNA-Seq, qPCR, and ELISA. Cetirizine, a histamine H1 receptor (H1R) antagonist, was used to treat the destabilization of the medial meniscus (DMM) mouse model of OA. ResultsFlow cytometry and immunohistology analysis of OA synovial cells revealed KIT+ FcεRI+ and TPSAB1+ mast cells. Single-cell RNA-Seq of OA synovial cells identified the expression of prototypical mast cell markers KIT, TPSAB1, CPA3 and HDC, as well as distinctive markers HPGD, CAVIN2, IL1RL1, PRG2, and CKLF, confirmed by bulk RNA-Seq and qPCR. A mast cell prototypical marker expression score classified 40 OA patients into three synovial pathotypes: mast cell-high, −medium, and -low. Additionally, we detected mast cell mediators including histamine, tryptase AB1, CPA3, PRG2, CAVIN2, and CKLF in OA synovial fluids. Elevated H1R expression was detected in human OA synovium, and treatment of mice with the H1 receptor antagonist cetirizine reduced the severity and OA-related mediators in DMM. ConclusionBased on differential expression of prototypical and distinct mast cell markers, human OA joints can be stratified into mast cell-high, −medium, and -low synovial tissue pathotypes. Pharmacologic blockade of histamine activity holds the potential to improve OA disease outcome.

Synovial membrane-derived mesenchymal progenitor cells from osteoarthritic joints in dogs possess lower chondrogenic-, and higher osteogenic capacity compared to normal joints

BackgroundSynovial membrane-derived mesenchymal progenitor cells (SM-MPCs) are a promising candidate for the cell-based treatment of osteoarthritis (OA) considering their in vitro and in vivo capacity for cartilage repair. However, the OA environment may adversely impact their regenerative capacity. There are no studies for canine (c)SM-MPCs that compare normal to OA SM-MPCs, even though dogs are considered a relevant animal model for OA. Therefore, this study compared cSM-MPCs from normal and OA synovial membrane tissue to elucidate the effect of the OA environment on MPC numbers, indicated by CD marker profile and colony-forming unit (CFU) capacity, and the impact of the OA niche on tri-lineage differentiation.MethodsNormal and OA synovial membrane were collected from the knee joints of healthy dogs and dogs with rupture of the cruciate ligaments. The synovium was assessed by histopathological OARSI scoring and by RT-qPCR for inflammation/synovitis-related markers. The presence of cSM-MPCs in the native tissue was further characterized with flow cytometry, RT-qPCR, and immunohistochemistry, using the MPC markers; CD90, CD73, CD44, CD271, and CD34. Furthermore, cells isolated upon enzymatic digestion were characterized by CFU capacity, and a population doublings assay. cSM-MPCs were selected based on plastic adherence, expanded to passage 2, and evaluated for the expression of MPC-related surface markers and tri-lineage differentiation capacity.ResultsSynovial tissue collected from the OA joints had a significantly higher OARSI score compared to normal joints, and significantly upregulated inflammation/synovitis markers S100A8/9, IL6, IL8, and CCL2. Both normal and OA synovial membrane contained cells displaying MPC properties, including a fibroblast-like morphology, CFU capacity, and maintained MPC marker expression over time during expansion. However, OA cSM-MPCs were unable to differentiate towards the chondrogenic lineage and had low adipogenic capacity in contrast to normal cSM-MPCs, whereas they possessed a higher osteogenic capacity. Furthermore, the OA synovial membrane contained significantly lower percentages of CD90+, CD44+, CD34+, and CD271+ cells.ConclusionsThe OA environment had adverse effects on the regenerative potential of cSM-MPCs, corroborated by decreased CFU, population doubling, and chondrogenic capacity compared to normal cSM-MPCs. OA cSM-MPCs may be a less optimal candidate for the cell-based treatment of OA than normal cSM-MPCs.

Identification and verification of ferroptosis-related genes in the synovial tissue of osteoarthritis using bioinformatics analysis.

Background: Osteoarthritis (OA) is a major factor causing pain and disability. Studies performed to date have suggested that synovitis is possibly a critical OA-related pathological change. Ferroptosis represents a novel type of lipid peroxidation-induced iron-dependent cell death. However, its effect on OA remains largely unclear. Objective: This work focused on identifying and validating the possible ferroptosis-related genes (FRGs) involved in synovitis of OA through bioinformatics analysis. Materials and Methods: The microarray dataset GSE55235 was downloaded in the database Gene Expression Omnibus (GEO). By the Venn diagram and GEO2R, differentially expressed genes (DEGs) and ferroptosis DEGs (FDEGs) were detected. DEGs were screened by GO and KEGG enrichment analysis, as well as protein-protein interaction (PPI) analysis. Besides, the software Cytoscape and database STRING were utilized to construct hub gene networks. Moreover, this study used the database NetworkAnalyst to predict the target miRNAs of the hub genes. Finally, the hub genes were confirmed by analysis of the receiver operating characteristic (ROC) curve on the GSE12021 and GSE1919 databases. Considering the relationship between ferroptosis and immunity, this study applied CIBERSORTx to analyze the immune infiltration in OA in addition. Results: This work discovered seven genes, including ATF3, IL6, CDKN1A, IL1B, EGR1, JUN, and CD44, as the hub FDEGs. The ROC analysis demonstrated that almost all hub genes had good diagnostic properties in GSE12021 and GSE 1919. Conclusion: This study discovered seven FDEGs to be the possible diagnostic biomarkers and therapeutic targets of synovitis during OA, which sheds more light on the pathogenesis of OA at the transcriptome level.

Assessment of disease activity in patients with rheumatoid arthritis using plasma tumour M2-pyruvate kinase test.

BackgroundPyruvate kinase M2 (PKM2) is an enzyme that regulates the final process of glycolysis and exists in tetrameric and dimeric forms. The dimeric form of PKM2, also known as tumour M2-PK, increases when aerobic glycolysis is augmented, a feature observed in rheumatoid arthritis (RA). We investigated whether plasma tumour M2-PK is elevated in patients with RA and whether its levels correlate with disease activity.MethodsPlasma levels of tumour M2-PK were measured for patients with RA (n=151), those with osteoarthritis (OA) (n=37), and controls (n=37). We evaluated the association between plasma tumour M2-PK and continuous variables using Pearson’s correlation analysis, and multivariate logistic regression analysis to determine the association between plasma tumour M2-PK and disease activity status. Knee synovial tissue blocks from patients with RA and OA were subjected to real-time quantitative PCR (qPCR) using two different primers for PKM2 and tumour M2-PK immunohistochemical (IHC) staining.ResultsThe tumour M2-PK level significantly correlated with the disease activity score in 28 joints (DAS28)-erythrocyte sedimentation rate (ESR) (r=0.546, p<0.001) and DAS28-C-reactive protein (CRP) (r=0.589, p<0.001). Moreover, repeat testing of tumour M2-PK levels in 20 patients revealed a significant decline in tumour M2-PK levels after reduction in inflammation (p<0.001). Area under the receiver operating characteristic curve (AUROC) analysis demonstrated that upon incorporation of tumour M2-PK, ESR, and CRP, the area under the curve was 0.962 for distinguishing moderate/high from remission/low disease activity. Adjusted logistic regression also revealed that a tumour M2-PK >43.9 U/mL (OR 3.672, p=0.042) independently predicted moderate/high disease activity status. Furthermore, tumour M2-PK levels in patients with RA were significantly higher than in those with OA and controls (all p<0.001). However, no differences were found in PKM2 expression in RA and OA synovial tissues as assessed by qPCR, and IHC analysis revealed negligible tumour M2-PK expression in the synovial tissues.ConclusionCirculating plasma tumour M2-PK levels may be a clinically useful indicator for evaluating disease activity and RA diagnosis.

Preliminary study on immune cells in the synovium of end-stage osteoarthritis and rheumatoid arthritis patients: neutrophils and IgG4-secreting plasma cells as differential diagnosis candidates

ObjectiveImmune cell evaluation could be useful for clarifying etiopathogenesis, providing a support for formulating the diagnoses of clinically similar joint pathologies or guiding indications for possible therapeutic targets. To contribute to differential diagnosis in joint pathologies we performed an immunophenotypical profile analyzing different immune cells in synovial tissues from patients with rheumatoid arthritis (RA) and osteoarthritis (OA). MethodsThe Krenn and immunologic synovitis (IMSYC) scores, which include the evaluation of T lymphocytes (CD3 positive), B lymphocytes (CD20), endothelial cells (CD31), macrophages (CD68) and proliferating cells (Ki-67 positive) were used to analyze the synovial tissue samples. Moreover, to corroborate immune activation, neutrophils (CD15 positive), NK cells (CD56 positive), plasma cells (CD138 positive), IgG4 and IgG4 secreting-CD138 cells were analyzed using immunohistochemical techniques. ResultsWe confirmed that all the samples had a high synovitis score according to both the Krenn and IMSYC scores. In both the RA and OA groups, we found similar scores for CD3 (T lymphocytes), CD20 (B lymphocytes), CD31 (endothelial cells), CD56 (NK cells), CD68 (macrophages) CD138 (plasma cells) and IgG4. In contrast, CD15 (neutrophils) was significantly higher in RA compared to OA. Interestingly, IgG4 secreting-CD138 cells were significantly higher in RA than OA, even if CD138 had the same score in both the RA and OA samples. ConclusionsThis study found that the scores for different immune cells were similar in both RA and OA synovial tissue with a high synovitis score. CD15 and IgG4 secreting-CD138 were the only immune cells with a higher score in RA compared to OA, suggesting a potential use for discriminating among pathologies with a high synovitis score.